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Machine Learning Engineer Quantization Jobs in Massachusetts

Bespoke Labs

Machine Learning Engineer

Worcester, MA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Red Hat, Inc.

Machine Learning Engineer

Boston, MA · On-site

$136.32 - $225.09/hr

## Machine Learning EngineerApplyremote type: Hybridlocations: Bostontime type: Full timeposted on ... Apply standard software engineering practices, including version control, code reviews, and ...

Amazon

Machine Learning Engineer, Alexa AI

Boston, MA · On-site

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation ...

Amazon

Machine Learning Engineer, Alexa AI

Boston, MA · On-site

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation ...

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Teradyne

Software Machine Learning Engineer

North Reading, MA · On-site

$116K - $186K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Opportunity Overview As a Machine Learning Engineer, you will design, develop, and deploy applied AI solutions with a good knowledge on graph machine learning, reinforcement learning, and ...

S&P Global

Machine Learning Engineer II

Cambridge, MA

$106K - $145K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization ...

Kensho Technologies LLC

Machine Learning Engineer II

Cambridge, MA · On-site

$106K - $145K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Machine Learning Engineer Quantization information

What does a machine learning engineer quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What are some common challenges machine learning engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a machine learning engineer quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What are popular job titles related to Machine Learning Engineer Quantization jobs in Massachusetts?

For Machine Learning Engineer Quantization jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in Massachusetts look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Massachusetts are:

What cities in Massachusetts are hiring for Machine Learning Engineer Quantization jobs?

Cities in Massachusetts with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

Bespoke Labs

Worcester, MA • On-site

Full-time

Re-posted 2 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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